Aerobic metabolic TCE degradation
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB89694 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR15000351_1.fastq.gz | Fastqsanger.gz | |||
| ERR15000351_2.fastq.gz | Fastqsanger.gz | |||
| ERR15000352_1.fastq.gz | Fastqsanger.gz | |||
| ERR15000352_2.fastq.gz | Fastqsanger.gz | |||
| ERR15000353_1.fastq.gz | Fastqsanger.gz |
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Project description:Low aerobic exercise capacity is a risk factor for diabetes and strong predictor of mortality; yet some individuals are exercise resistant, and unable to improve exercise capacity through exercise training. To test the hypothesis that resistance to aerobic exercise training underlies metabolic disease-risk, we used selective breeding for 15 generation to develop rat models of low- and high-aerobic response to training. Before exercise training, rats selected as low- and high-responders had similar exercise capacities. However, after 8-wks of treadmill training low-responders failed to improve their exercise capacity, while high-responders improved by 54%. Remarkably, low-responders to aerobic training exhibited pronounced metabolic dysfunction characterized by insulin resistance and increased adiposity, demonstrating that the exercise resistant phenotype segregates with disease risk. Low-responders had impaired exercise-induced angiogenes0is in muscle; however, mitochondrial capacity was intact and increased normally with exercise training, demonstrating that mitochondria are not limiting for aerobic adaptation or responsible for metabolic dysfunction in low-responders. Low-responders had increased stress/inflammatory signaling and altered TGFM-NM-2 signaling, characterized by hyperphosphorylation of a novel exercise-regulated phosphorylation site on SMAD2. Using this powerful biological model system we have discovered key pathways for low exercise training response that may represent novel targets for the treatment of metabolic disease. Cardiac and skeletal muscle from 3 high and 3 low responder rats were examined for differential miRNA expression using Exiqon microarrays
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Project description:Low aerobic exercise capacity is a risk factor for diabetes and strong predictor of mortality; yet some individuals are exercise resistant, and unable to improve exercise capacity through exercise training. To test the hypothesis that resistance to aerobic exercise training underlies metabolic disease-risk, we used selective breeding for 15 generation to develop rat models of low- and high-aerobic response to training. Before exercise training, rats selected as low- and high-responders had similar exercise capacities. However, after 8-wks of treadmill training low-responders failed to improve their exercise capacity, while high-responders improved by 54%. Remarkably, low-responders to aerobic training exhibited pronounced metabolic dysfunction characterized by insulin resistance and increased adiposity, demonstrating that the exercise resistant phenotype segregates with disease risk. Low-responders had impaired exercise-induced angiogenes0is in muscle; however, mitochondrial capacity was intact and increased normally with exercise training, demonstrating that mitochondria are not limiting for aerobic adaptation or responsible for metabolic dysfunction in low-responders. Low-responders had increased stress/inflammatory signaling and altered TGFβ signaling, characterized by hyperphosphorylation of a novel exercise-regulated phosphorylation site on SMAD2. Using this powerful biological model system we have discovered key pathways for low exercise training response that may represent novel targets for the treatment of metabolic disease.
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Project description:Chlorophyll degradation by aerobic marine bacterium
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Project description:Transcription was arrested using 50 ug/ul of rifampin leaving RNA degradation as the sole vector responsible for mRNA abundance. mRNA half-lives were calculated from the decay of signal intensity from T0. Four replicates were sampled after 0, 5 10, 15, 20, and 30 minutes of mRNA decay for a total of 24 arrays.
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